A Multi Hidden Recurrent Neural Network with a Modified Grey Wolf Optimizer

Identifying university students' weaknesses results in better learning and can function as an early warning system to enable students to improve. However, the satisfaction level of existing systems is not promising. New and dynamic hybrid systems are needed to imitate this mechanism. A hybrid system (a modified Recurrent Neural Network with an adapted Grey Wolf Optimizer) is used to forecast students' outcomes. This proposed system would improve instruction by the faculty and enhance the students' learning experiences. The results show that a modified recurrent neural network with an adapted Grey Wolf Optimizer has the best accuracy when compared with other models.Comment: 34 pages, published in PLoS ON

An evaluation of farm credit systems in the U.S.A. and Pakistan

"In modern farming, as in other businesses, the key to a satisfactory money income is a proper combination of productive assets, such as land, livestock, and machinery with available labor and managerial ability. The amount of capital a farm family controls, the terms and conditions under which it is obtained, and the way it is used determine in large degree the level of income. Lending institutions play very important roles in macro-financial policies. The government plays a direct role by establishing lending institutions (the Farm Credit System and the Farmers Home Administration) and otherlending programs in general. Both Federal and State governments play an indirect role through legislation and, in turn, through supervisory agencies such as the Federal Reserve System. Micro-finaneial aspects of agricultural finance pertains to the individual farm. It includes those parts of capital in farm management which relate to acquisition and use of capital in the farm business."--Introduction.Includes bibliographical references

Image Processing with Dipole-Coupled Nanomagnets: Noise Suppression and Edge Enhancement Detection

Hardware based image processing offers speed and convenience not found in software-centric approaches. Here, we show theoretically that a two-dimensional periodic array of dipole-coupled elliptical nanomagnets, delineated on a piezoelectric substrate, can act as a dynamical system for specific image processing functions. Each nanomagnet has two stable magnetization states that encode pixel color (black or white). An image containing black and white pixels is first converted to voltage states and then mapped into the magnetization states of a nanomagnet array with magneto-tunneling junctions (MTJs). The same MTJs are employed to read out the processed pixel colors later. Dipole interaction between the nanomagnets implements specific image processing tasks such as noise reduction and edge enhancement detection. These functions are triggered by applying a global strain to the nanomagnets with a voltage dropped across the piezoelectric substrate. An image containing an arbitrary number of black and white pixels can be processed in few nanoseconds with very low energy cost